Showing 41 - 60 results of 4,823 for search '(( algorithm within function ) OR ((( algorithm python function ) OR ( algorithms a function ))))', query time: 0.45s Refine Results
  1. 41

    Fitness comparison on test function. by Kejia Liu (5699651)

    Published 2025
    “…The study employed traditional benchmark functions and conducted evaluations versus baselines Standard GEP, NMO-SARA, and MS-GEP-A to assess fitness outcomes, R² values, population diversification, and the avoidance of local optima. …”
  2. 42

    A comparison of whether to add a penalty. by Dawei Wang (471687)

    Published 2025
    “…An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”
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    NRPStransformer, an Accurate Adenylation Domain Specificity Prediction Algorithm for Genome Mining of Nonribosomal Peptides by Zhihan Zhang (1403308)

    Published 2025
    “…Leveraging the sequences within the flavodoxin-like subdomain, we developed a substrate specificity prediction algorithm using a protein language model, achieving 92% overall prediction accuracy for 43 frequently observed amino acids, significantly improving the prediction reliability. …”
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    Multimodal reference functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
  7. 47

    R-squared comparison of test function. by Kejia Liu (5699651)

    Published 2025
    “…The study employed traditional benchmark functions and conducted evaluations versus baselines Standard GEP, NMO-SARA, and MS-GEP-A to assess fitness outcomes, R² values, population diversification, and the avoidance of local optima. …”
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    The convergence curves of the test functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
  14. 54

    Single-peaked reference functions. by Ruiyu Zhan (21602031)

    Published 2025
    “…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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